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MEMORY: A Matrix-based Efficient Semantic Web Service Discovery System

机译:内存:基于矩阵的高效语义Web服务发现系统

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With the advance of Semantic Web, the adoption of Semantic Web has been regarded as the most promising way to improve the recall rate and precision rate of service discovery. However, Semantic Web Service discovery (SWS) is essentially not used on a large scale in real business world due to its time-consuming performance and weak support for the QoS-based discovery. In order to solve these problems, this paper presents a matrix-based efficient SWS discovery system, namely MEMORY. MEMORY does ontological pre-reasoning and holds the reasoning results in matrix forms in service publishing phase, so that it can transfer the load of semantic reasoning from service query to service publication and perform fast matching during service discovery. The experiments in the end are conducted to further demonstrate the feasibility of our proposed matching approach and its high efficiency.
机译:通过语义网络的进步,通过语义网络的采用被认为是提高召回率和服务精度发现的最有希望的方法。然而,由于其耗时的性能和对基于QoS的发现的支持,语义Web服务发现(SWS)基本上并非在真实商业世界中使用大规模。为了解决这些问题,本文介绍了基于矩阵的高效SWS发现系统,即内存。内存可以在服务发布阶段中的矩阵形式的矩阵形式进行本体预推理,使其可以将语义推理的负载从服务查询转移到服务发布,并在服务发现期间执行快速匹配。终点的实验进一步证明了我们提出的匹配方法的可行性及其高效率。

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